The load planning problem of motor carriers: Problem description and a proposed solution approach

1983 ◽  
Vol 17 (6) ◽  
pp. 471-480 ◽  
Author(s):  
Warren B. Powell ◽  
Yosef Sheffi
Keyword(s):  
Planning Problem ◽  
Solution Approach ◽  
Motor Carriers ◽  
Load Planning ◽  
Problem Description

scholarly journals Efficient Solution Approach to Maximum Flow Evacuation Planning Problem without Flow Conservation Aspect

2018 ◽  
Vol 13 (1) ◽  
pp. 108-116
Author(s):  
Phanindra Prasad Bhandari ◽  
Shree Ram Khadka
Keyword(s):  
Network Flow ◽  
Efficient Solution ◽  
Maximum Flow ◽  
Evacuation Planning ◽  
Planning Problem ◽  
Intermediate Node ◽  
Solution Approach ◽  
Solution Strategies ◽  
Source Sink ◽  
Flow Conservation

 An attempt of shifting as more people as possible and/or their logistics from a dangerous place to a safer place is an evacuation planning problem. Such problems modeled on network have been extensively studied and the various efficient solution procedures have been established. The solution strategies for these problems are based on source-sink path augmentation and the flow function satisfies the flow conservation at each intermediate node. Besides this, the network flow problem in which flow may not be conserved at node necessarily could also be used to model the evacuation planning problem. This paper proposes a model for maximum flow evacuation planning problem on a single-source-single-sink static network with integral arc capacities with holding capability of evacuees in the temporary shelter at intermediate nodes and extends the model into the dynamic case. Journal of the Institute of Engineering, 2017, 13(1): 108-116

Pareto Optimal Solution Selection for a Multi-Site Supply Chain Planning Problem Using the VIKOR and TOPSIS Methods

2017 ◽  
Vol 8 (3) ◽  
pp. 21-39 ◽  
Author(s):  
Houssem Felfel ◽  
Omar Ayadi ◽  
Faouzi Masmoudi
Keyword(s):  
Supply Chain ◽  
Optimal Solution ◽  
Quality Level ◽  
Planning Problem ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Compromise Solution ◽  
Optimal Solutions ◽  
Pareto Solution ◽  
Solution Approach

In this paper, a multi-objective, multi-product, multi-period production and transportation planning problem in the context of a multi-site supply chain is proposed. The developed model attempts simultaneously to maximize the profit and to maximize the product quality level. The objective of this paper is to provide the decision maker with a front of Pareto optimal solutions and to help him to select the best Pareto solution. To do so, the epsilon-constraint method is adopted to generate the set of Pareto optimal solutions. Then, the technique for order preference by similarity to ideal solution (TOSIS) is used to choose the best compromise solution. The multi-criteria optimization and compromise solution (VIKOR), a commonly used method in multiple criteria analysis, is applied in order to evaluate the selected solutions using TOPSIS method. This paper offers a numerical example to illustrate the solution approach and to compare the obtained results using TOSIS and VIKOR methods.

scholarly journals New solution approaches for the train load planning problem

2019 ◽  
Vol 8 (3) ◽  
pp. 299-325
Author(s):  
Daniela Ambrosino ◽  
Claudia Caballini
Keyword(s):  
Planning Problem ◽  
Load Planning

scholarly journals Solving the Torpedo Scheduling Problem

2019 ◽  
Vol 66 ◽  
pp. 1-32
Author(s):  
Martin Josef Geiger ◽  
Lucas Kletzander ◽  
Nysret Musliu
Keyword(s):  
Material Flow ◽  
Simulated Annealing Algorithm ◽  
Steel Production ◽  
Experimental Investigations ◽  
Planning Problem ◽  
Scheduling Problem ◽  
Solution Approach ◽  
Annealing Algorithm ◽  
Problem Instances ◽  
Continuous Material

The article presents a solution approach for the Torpedo Scheduling Problem, an operational planning problem found in steel production. The problem consists of the integrated scheduling and routing of torpedo cars, i. e. steel transporting vehicles, from a blast furnace to steel converters. In the continuous metallurgic transformation of iron into steel, the discrete transportation step of molten iron must be planned with considerable care in order to ensure a continuous material flow. The problem is solved by a Simulated Annealing algorithm, coupled with an approach of reducing the set of feasible material assignments. The latter is based on logical reductions and lower bound calculations on the number of torpedo cars. Experimental investigations are performed on a larger number of problem instances, which stem from the 2016 implementation challenge of the Association of Constraint Programming (ACP). Our approach was ranked first (joint first place) in the 2016 ACP challenge and found optimal solutions for all used instances in this challenge.

scholarly journals An Exact Solution Approach for the Bus Line Planning Problem with Integrated Passenger Routing

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Evert Vermeir ◽  
Wouter Engelen ◽  
Johan Philips ◽  
Pieter Vansteenwegen
Keyword(s):  
Optimal Solution ◽  
Combinatorial Problem ◽  
Network Design Problem ◽  
Planning Problem ◽  
Optimal Solutions ◽  
Line Planning ◽  
Solution Approach ◽  
Benchmark Instances ◽  
Transit Network Design ◽  
Passenger Routing

The bus line planning problem or transit network design problem with integrated passenger routing is a challenging combinatorial problem. Although well-known benchmark instances for this problem have been available for decades, the state of the art lacks optimal solutions for these instances. The branch and bound algorithm, presented in this paper, introduces three novel concepts to determine these optimal solutions: (1) a new line pool generation method based on dominance, (2) the introduction of essential links, i.e., links which can be determined beforehand and must be present in the optimal solution, and (3) a new network representation based on adding only extra edges. Next to presenting the newly obtained optimal solutions, each of the abovementioned concepts is examined in isolation in the experiments, and it is shown that they contribute significantly to the success of the algorithm.

scholarly journals Workforce Scheduling with Order-Picking Assignments in Distribution Facilities

2021 ◽  
Author(s):  
Arpan Rijal ◽  
Marco Bijvank ◽  
Asvin Goel ◽  
René de Koster
Keyword(s):  
Time Windows ◽  
Real Life ◽  
Labor Cost ◽  
Order Picking ◽  
Planning Problem ◽  
Scheduling Problem ◽  
Workforce Scheduling ◽  
Solution Approach ◽  
Business Application ◽  
End Times

Scheduling the availability of order pickers is crucial for effective operations in a distribution facility with manual order pickers. When order-picking activities can only be performed in specific time windows, it is essential to jointly solve the order picker shift scheduling problem and the order picker planning problem of assigning and sequencing individual orders to order pickers. This requires decisions regarding the number of order pickers to schedule, shift start and end times, break times, as well as the assignment and timing of order-picking activities. We call this the order picker scheduling problem and present two formulations. A branch-and-price algorithm and a metaheuristic are developed to solve the problem. Numerical experiments illustrate that the metaheuristic finds near-optimal solutions at 80% shorter computation times. A case study at the largest supermarket chain in The Netherlands shows the applicability of the solution approach in a real-life business application. In particular, different shift structures are analyzed, and it is concluded that the retailer can increase the minimum compensated duration for employed workers from six hours to seven or eight hours while reducing the average labor cost with up to 5% savings when a 15-minute flexibility is implemented in the scheduling of break times.

scholarly journals Application of Two-Phase Fuzzy Optimization Approach to Multiproduct Multistage Integrated Production Planning with Linguistic Preference under Uncertainty

2015 ◽  
Vol 2015 ◽  
pp. 1-20 ◽  
Author(s):  
Shan Lu ◽  
Hongye Su ◽  
Lian Xiao ◽  
Li Zhu
Keyword(s):  
Production Planning ◽  
Programming Model ◽  
Fuzzy Optimization ◽  
Service Level ◽  
Mixed Integer ◽  
Planning Problem ◽  
Optimization Approach ◽  
Two Phase ◽  
Steel Rolling ◽  
Solution Approach

This paper tackles the challenges for a production planning problem with linguistic preference on the objectives in an uncertain multiproduct multistage manufacturing environment. The uncertain sources are modelled by fuzzy sets and involve those induced by both the epistemic factors of process and external factors from customers and suppliers. A fuzzy multiobjective mixed integer programming model with different objective priorities is proposed to address the problem which attempts to simultaneously minimize the relevant operations cost and maximize the average safety stock holding level and the average service level. The epistemic and external uncertainty is simultaneously considered and formulated as flexible constraints. By defining the priority levels, a two-phase fuzzy optimization approach is used to manage the preference extent and convert the original model into an auxiliary crisp one. Then a novel interactive solution approach is proposed to solve this problem. An industrial case originating from a steel rolling plant is applied to implement the proposed approach. The numerical results demonstrate the efficiency and feasibility to handle the linguistic preference and provide a compromised solution in an uncertain environment.

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